Congenital malformations are the major cause of infant mortality in the US and Europe. However, we have a poor understanding of the genetic causes of congenital malformations. In order to discover these genetic causes, we and others have employed human genomics analyses on patients. In particular we have focused on Heterotaxy, a disorder of left-right patterning. Normally, our internal organs are asymmetrically distributed along the left-right axis and failure to do so can lead to severe disease including congenital heart disease, gut malrotation, and immune deficiencies. Human genetic analysis of these patients has identified many candidate genes, but the functional relevance of these genes is unclear since strong genetic evidence (second unrelated alleles) is not available for most of them. In addition, these genes are diverse and do not fall into clear pathways~ in fact, the vast majority of these candidate genes are novel to left-right patterning. For this reason, we propose a systems approach to the analysis of these heterotaxy candidate genes. We will first prioritize these genes based on available genetic evidence and then use an unbiased approach, which will include gene expression, gain of function, and loss of function analysis to determine which of these genes play a role in left- right patterning using our high-throughput model, Xenopus. Our preliminary results indicate that many but not all of these candidate genes are important for left-right patterning. Then we will take an unbiased systems approach to placing these heterotaxy candidate genes into the left-right signaling gene regulatory network. Our preliminary results demonstrate that this systems approach identifies unexpected and interesting bridges between different pathways and identifies functions not otherwise expected of known gene and identifies specific functions of genes with no known function. In this way, we hope to improve our understanding of heterotaxy and develop a general model to approach many congenital malformations.